DocumentCode :
2340611
Title :
Real-time cognitive technical systems, a learning material processing system, social and future aspects
Author :
Wersborg, Ingo Stork genannt ; Borgwardt, Felix ; Diepold, Klaus
Author_Institution :
Dept. of Electr. Eng. & Inf. Technol., Tech. Univ. Munchen, Munich, Germany
fYear :
2009
fDate :
23-25 Nov. 2009
Firstpage :
145
Lastpage :
152
Abstract :
Most of the robots today are used in production systems and the potential for assistive robots is high. Therefore, this paper demonstrates an architecture for real-time cognitive technical systems that are applicable for assistive and production robots with at least two sensor data input streams and one actuator to be controlled. An application of this architecture can be demonstrated by using a robotic production system that learns from a human expert, using different dimensionality reduction and classifier techniques such as Isometric feature mapping, Support Vector Machines, and Fuzzy k-Nearest Neighbor classification. This paper also contains a social study on the impact of research in Artificial Intelligence (AI) and cognitive technical systems. The study offers a synopsis of the history of AI and forecasts the social impact that intelligent robotic assistance has on the areas of automotive, medical care, production systems, and private homes.
Keywords :
artificial intelligence; cognitive systems; fuzzy set theory; industrial robots; pattern classification; production engineering; real-time systems; support vector machines; artificial intelligence; assistive robots; fuzzy k-nearest neighbor classification; learning material processing system; real-time cognitive technical systems; robotic production system; social aspects; social impact; support vector machines; Laser beam cutting; Power lasers; Robot sensing systems; Support vector machines; Surface emitting lasers; Welding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Robotics and its Social Impacts (ARSO), 2009 IEEE Workshop on
Conference_Location :
Tokyo
Print_ISBN :
978-1-4244-4393-2
Electronic_ISBN :
978-1-4244-4394-9
Type :
conf
DOI :
10.1109/ARSO.2009.5587056
Filename :
5587056
Link To Document :
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